Biomarker identification for prediction of diabetes
Biomarkers are the naturally occurring biological molecules, which help in measuring some biological state or condition. These find application in screening or diagnosis of diabetes such as for glucose hemoglobin tests for type-2 diabetes. Simultaneously, treatment management also forms another application sphere.
An ideal biomarker tends to improve the identification of those at risk of diabetes occurrence or advancement. Besides risk identification, it should also help refine complication prediction, and assist in treatment customization. For example, the standard and serial data on biomarkers arising from liver have unraveled the role of hepatic fat in the pathogenesis of diabetes. Further, a novel branch chain amino acid marker, known to play role in insulin resistance, could also facilitate the prediction of type 2 diabetes risk. Biomarker research is yet to reveal the relevance of alterations in biomarkers with time in individual patients. Long-term impact of such alterations on treatment outcomes demands an investigation. Environmental factors may also play a role in determining the concentration of biomarkers in human body. The environmental effects are perceived to alter the association between biomarkers and type-2 diabetes.
According to some studies, the behavioural factors such as increased physical inactivity or increased carbohydrate intake also tend to modify the concentration of biomarkers. This necessitates the consideration of implementing tailored diagnostic and prevention strategies. However, novel biomarkers might not necessarily advance the prediction of new-onset diabetes, with respect to the conventional measures combined with HbA(1c).